The present invention generally relates to methods of monitoring the health and growth of plants. More particularly, this invention relates to aerial imaging of vegetation to determine, monitor, and predict plant health and growth.
Various technologies have been used in the past to measure temperature of plant leaves. For example, U.S. Pat. No. 7,058,197 uses visual light reflectance to generate NDVI (normalized difference vegetation index) images. This patent relies on reflected light from the sun, and therefore teaches that the optimum time for image acquisition using the disclosed process is within two hours of “solar noon” and on cloudless days. This makes it very impractical for a commercial application. In particular, this patent discloses                Aerial imagery was collected four times throughout the growing season. The image dates correlated with bare soil, VI2, VT, and R4 crop stages (see section on “Resolutions in Remote Sensing”). The aerial imagery was flown with digital cameras with an array size of approximately 1500 pixels wide and 1000 pixels in the along track dimension. The digital systems were 8-bit systems and were collected and stored on an on-board computer in a Tagged Image Format (TIF). Four bands were collected representing the blue, green, red, and near infrared portions of the electromagnetic spectrum (see section on “Spectral Nature of Remote Sensing”). The cameras were aligned in a two-by-two matrix and were rigid mounted (pseudo-bore sited) with the lenses focussed [sic] on infinity. The imagery was flown at approximately 5000 feet above ground level (AGL) to produce a spatial resolution of approximately one meter by one meter (see section on “Resolutions in Remote Sensing”). The digital cameras have square pixels and are not interlaced during image acquisition. The optimum time for image acquisition was two hours before or two hours after solar noon (see section on “Resolutions in Remote Sensing”). Images were not acquired during times of poor atmospheric conditions (haze, rain, clouds). No cloud shadows were acceptable in the imagery.        
In addition, it appears that the methodology disclosed by U.S. Pat. No. 7,058,197 is only able to indicate that a problem exists after a plant has actually changed its structure, as indicated by its color. In many cases, this is too late to take corrective action. Column 6 of U.S. Pat. No. 7,058,197 describes the extent of the methodology's capability as follows:                The third major division of the electromagnetic spectrum ranges from around 1500 nanometers to approximately 3000 nanometers and is referred to as the middle-infrared. It is this portion of the electromagnetic spectrum where moisture plays a dominant role. Although other factors such as organic matter, iron content, and clay content have an effect, moisture appears be the primary mechanism affecting reflectance. More specifically, the higher the moisture content, the lower the reflectance. As objects lose moisture or begin to dry, their reflectance in this portion of the electromagnetic spectrum increases. While this concept has been proven in a laboratory setting, applying this concept in practice has been somewhat evasive.        
As another example, U.S. Pat. No. 6,597,991 uses thermal imaging to detect water content in leaves for irrigation purposes. This patent is reliant on obtaining actual temperatures and using ground-based references for calibration. Arguably, a significant disadvantage of U.S. Pat. No. 6,597,991 is its reliance on extremely accurate temperature measurements so that the need for irrigation can be determined. Such a requirement necessitates an extra step and additional costs associated with the calibration. U.S. Pat. No. 6,597,991 does not appear to contain a reference to the detection of disease in very early stages.
U.S. Pat. No. 6,212,824 uses various remote sensing and image analysis technologies for classifying plants in small fields. In particular, this patent discloses                The present invention employs remote sensing technology to classify inbred and hybrid plants and segregating populations for commercially important traits such as yield, environmental stress responses, disease resistance, insect and herbicide resistance, and drought resistance. Images are prepared from remote sensing data obtained from plants.        These evaluations are useful in decision making to select plants from early generations or preliminary tests used in breeding, to be advanced for selective breeding.        
U.S. Pat. No. 6,212,824 discloses the use of both thermal imaging and reflectance at various wavelengths (multiple bands) for imaging vegetation from an aircraft in order to classify plants. However, it does not appear that the patent uses long-wave thermal images of a type capable of use for monitoring the growth of vegetation, predicting future growth of vegetation, and/or detecting disease, insect infestation, or other stress factors in vegetation before they become apparent to visual or near-infrared cameras. Rather the patent appears to focus on visual and near-infrared wavelengths. For example, the patent states                In an exemplary embodiment, CIR photographs revealed qualitative differences between the four row subplots across both limited and full irrigation treatments (FIG. 4). These photographs were subsequently processed (FIG. 5) to generate quantified values for the three bands or wavelengths of reflectance used to create the photograph. The three bands 20 were green, red and near-infrared (not thermal) portions of the energy spectrum. FIGS. 6-8 show the green, red and near-infrared results on the same field as in FIG. 4. The red and near-infrared bands were considered to be indications of the crop conditions, having been used by others in crop assessment programs. The red band corresponds to chlorophyll absorption and, according to theory, reflectance in this band increases during times of stress. Reflectance in the near-infrared region is predicted to decrease with increasing stress. The near-infrared region is believed to be related to plant structure and composition.        
In view of the above, it can be appreciated that there are certain problems, shortcomings or disadvantages associated with the prior art, and that it would be desirable if an improved method were available for aerial monitoring of plant health and growth that does not rely solely on sensing reflected visible light and/or ground-based measurements.